Big Data Analytics: Are You Ready?

Big Data Analytics: Are You Ready?

Ms. Lind has over 43 years in the data processing and industrial psychology arenas and has published extensively on performance, system implementation, risk evaluation and programming productivity subjects, as well as conducted considerable research in the performance modeling and tuning areas.

Michael D. Kowolenko, Ph.D.

Industrial Fellow, Center for Innovation Management Studies (CIMS)

NC State University, Poole College of Management

Michael D. Kowolenko, Ph.D.

Dr. Michael Kowolenko is currently an Industrial Fellow at the Center for Innovation Management Studies (CIMS)based in the NC State Poole College of Management. His research is focused on the interface of technology and business decision making. Prior to joining CIMS, Kowolenko was senior vice president of Wyeth Biotech Technical Operations and Product Supply (TO&PS), providing strategic and operations leadership perspective to ongoing integrated and cross-functional global business decisions.

Robert Friske

Power Systems Global Marketing Manager

IBM

Robert Friske

Bob Friske has almost three decades of experience with IBM, half of that time as an IBM Marketing Manager and half as an IBM customer working for one of the big three auto companies in Michigan. Since joining IBM, Bob has worked for both IBM Storage Systems and IBM Power Systems helping the brands bring smarter computing solutions to market that help clients reduce costs, enable new workloads, and deliver exceptional client experience.

Business leaders are seeking the business insights, market share, and revenue growth promised by the rise of big data analytics. The opportunity and adoption of big data analytics presents real challenges to IT leaders as the influx of unstructured data radically increases the demand for IT resources. Solitaire Interglobal Ltd studied 31,000+ client deployments to isolate infrastructure characteristics from both a net business effect and raw performance perspective.

Attend this webinar to learn:

How demand for IT resources increases in each stage of a big data analytics solution deployment.

The top metrics IT organizations use to measure the ability to handle demand, and quickly get ROI from big data projects.